Price Recommendation Engine
Maximising Share By Setting the Right Price
The sales team was faced with an increasingly competitive market. They needed a solution that could help price their products effectively and maximise its market share. They also needed to be able to respond to the competition’s action fast.
“This was a fundamental shift in our company on how we have worked before to deliver reports and insights to business.
Both locally and regionally, this is recognized as a ‘truly innovative initiative’, adding significant value to the business and providing a platform for enabling future capabilities.”
Reporting & Insights Lead
Do I need to discount?
One the most common challenges in retail business is to establish an optimal pricing strategy. Applying discounts in favour of gaining revenue is a tricky act of balance. You have to consider many factors in order to find the right price. This is a lengthy and expensive task. The traditional approach is less responsive to evolving market conditions. Besides, they require
How will my competition react?
Pricing isn’t static because it is strongly influenced by what your competitors do. Modelling competition requires large amounts of data and frequent validation. Keeping track of what competitors do is a costly and difficult operation.
Price Recommendation Engine helps find the right price automatically
AgileBI built a price recommendation engine to automate deriving the optimum price. We created an engine that takes care of everything from modelling the demand, computing price elasticity down to quantifying influence from competitions. Powering the engine is a range of sophisticated maths and analytics techniques.
We also created an ability for a user to specify what competitors would do. The engine adjusts the price point accordingly. This way,
Results and future plans
The sales team now have an automated and responsive model that suggests the price at which revenue can be maximised.
The next step is to incorporate external data such as weather and census. This allows the model to be able to understand the impact that weather has on the optimal price.